Ling Li

7.5k citations
406 papers · 5.8k · 2 hit papers · h-index 35

Impact in

Papers in

Ling Li

367 papers receiving 5.6k citations

Ling Li's Hit Papers

Structural damage identification based on autoencoder neural networks and deep learning 2018 · 323 citations
3230+4+9Years since publication100200300400

Peers

Ling Li
Comparison fields: 5 of 210
  • Biomaterials 734
  • Computer Vision and Pattern Recognition 1.1k
  • Civil and Structural Engineering 995
  • Process Chemistry and Technology 98
  • Pollution 322
Replace Ning Wang with:
Ning Wang China
Xin Chen China
Han Wang China
Yan Wang China
Lijuan Wang China
Jianqiang Li China
Liming Chen United Kingdom
Xiaoqi Chen China
Bin Jiang China
Huihui Wang China
Ling Li relative to Ning Wang China Ning Wang's profile →
Citations per field
00.5×1.5×2.3×
Ning Wang · 1×
Citations per year

Countries citing papers authored by Ling Li

Since Specialization
Citations

This map shows the geographic impact of Ling Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ling Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Li more than expected).

Fields of papers citing papers by Ling Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ling Li. The network helps show where Ling Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Ling Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ling Li Line = papers co-authored together Ling Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 406 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Hit paper breakdown →
2012490
2 2014433
3
Structural damage identification based on autoencoder neural networks and deep learning
Hit paper breakdown →
2018323
4 2019155
5 2008136
6 2015129
7 2018121
8 2019112
9 2021112
10 202290
11 200886
12 200383
13 201178
14 200873
15 201969
16 201660
17 202056
18 202155
19 201053
20 201752

About Ling Li

Ling Li is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence, Civil and Structural Engineering and Computational Mechanics, having authored 406 papers that have together received 5.8k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (35 papers), Face and Expression Recognition (29 papers), Human Pose and Action Recognition (28 papers), Video Surveillance and Tracking Methods (24 papers), Structural Health Monitoring Techniques (21 papers), Advanced Image Processing Techniques (19 papers), Computer Graphics and Visualization Techniques (19 papers) and 3D Shape Modeling and Analysis (19 papers). The work is most often cited by research in Biomaterials (734 citations), Computer Vision and Pattern Recognition (1.1k citations), Civil and Structural Engineering (995 citations), Process Chemistry and Technology (98 citations) and Pollution (322 citations). Ling Li has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Hong Hao, Wanquan Liu, Qilin Li, Jun Li, Bilal Fadlallah, Sohan Seth, Austin J. Brockmeier, A. Keil, José C. Prı́ncipe and Chathurdara Sri Nadith Pathirage. Their work appears in journals such as Engineering Structures, Computers & Graphics, Pattern Recognition Letters, Multimedia Tools and Applications and Structural Control and Health Monitoring.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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